Staff Software Engineer, AI/ML, ML Infrastructure, Search Ads

Google•Pittsburgh, PA

4h•$207,000 - $300,000

About The Position

Google software engineers develop technologies that enable billions of users to connect, explore, and interact with information. In this role, you will work on projects important to Google, with opportunities to move between teams and projects as the business evolves. You will apply technical expertise to manage project priorities, deadlines, and deliverables, and design, develop, test, deploy, maintain, and enhance software solutions. Google Ads applies machine learning and Generative AI models, including Gemini, to power its global advertising business. The work affects billions of users through efforts to protect users, improve ad quality, and optimize advertiser return on investment. The role involves close collaboration with teams such as Google Research and DeepMind to address complex challenges and build advertising technology at scale.

Requirements

Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
5 years of experience leading machine learning design and optimizing end-to-end machine learning, such as model deployment, model evaluation, data processing, and debugging.
2 years of experience with state-of-the-art Generative AI techniques, such as LLMs, multimodal models, and large vision models, or with related concepts such as language modeling and computer vision.
Experience building and architecting machine learning systems and infrastructure for model training, evaluation, deployment, or serving.
Experience designing and operating distributed computing systems for large-scale AI/ML workloads.

Nice To Haves

Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
8 years of experience with data structures and algorithms.
3 years of experience in a technical leadership role leading project teams and setting technical direction.
3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.
Experience in machine learning modeling, specifically with Large Language Models (LLMs).
Experience in distributed machine learning system design.

Responsibilities

Research emerging technology and make trade-off decisions between immediate wins and long-term stability.
Modify training and serving infrastructure to support new modeling techniques and products.
Collaborate closely with team members and partners to build systems that integrate seamlessly across the ecosystem.
Improve the robustness, reliability, and usability of machine learning infrastructure.
Engage with modeling teams to explore pain points and identify novel use cases.
Manage project priorities, deadlines, and deliverables.
Design, develop, test, deploy, maintain, and enhance software solutions.